Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas
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Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas
This practical, hands-on guide empowers you to build and deploy powerful time series forecasting models.
Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas
Mahsulot #: 104729386

Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas

89% of respondents would recommend this to a friend

Mahsulot #: 104729386

UZS 995189

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This practical, hands-on guide empowers you to build and deploy powerful time series forecasting models.
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What Stands Out

Comprehensive Coverage
This book offers an in-depth exploration of time series forecasting techniques, integrating both machine learning and deep learning approaches using PyTorch and pandas, catering to industry needs.
Hands-On Approach
Readers engage in practical, hands-on projects to solidify concepts, ensuring skills are directly applicable in real-world scenarios, making it invaluable for professionals looking to enhance their forecasting prowess.
Future-Proof Skills
By focusing on modern tools and methodologies in time series analysis, the book equips readers with relevant skills necessary for evolving industry demands, thereby enhancing their career prospects in data science.

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Shop Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas online at a best price in Oʻzbekiston. B0D6G3SHD6
Publisher Packt Publishing
Publication date 31 Oct. 2024
Edition 2nd
Language English
Print length 658 pages
ISBN-10 1835883184
ISBN-13 978-1835883181
Item weight 1.12 kg
Dimensions 19.05 x 3.78 x 23.5 cm

Who Should Buy?

Suitable For
  • Data Scientists

    Ideal for data scientists looking to enhance their skills in time series analysis with advanced machine learning techniques.

  • Machine Learning Engineers

    Perfect for professionals seeking to apply deep learning methodologies to time series forecasting projects in various industries.

  • Students and Learners

    Beneficial for students studying data science who want practical knowledge of time series analysis using Python, PyTorch, and pandas.

Not Suitable For
  • Beginners

    Not suitable for complete beginners, as prior knowledge of Python and basic statistics is typically needed to grasp concepts.

MAHSULOT TAVSIFI

Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas

Savolingiz bormi? Biz bilan suhbatlashish

Xaridor savollari va javoblari

  • Savol: What prior knowledge is needed to use this book?

    Javob: A basic understanding of statistics and Python programming is recommended.
  • Savol: Is this book suitable for beginners?

    Javob: Yes, it starts with fundamental concepts before progressing to advanced topics.
  • Savol: Can I use this book for practical applications in my job?

    Javob: Absolutely, it provides industry-ready techniques and strategies for real-world forecasting problems.

Higher Education Editorial Review

Modern Time Series Forecasting With Python Industry-ready Machine Learning And Deep Learning Time Series Analysis With PyTorch And Pandas is an essential resource for anyone looking to dive into time series analysis. With 658 pages of comprehensive content published by Packt Publishing, this 2nd edition provides in-depth knowledge suitable for both beginners and experienced practitioners. The inclusion of PyTorch and Pandas enhances the application of machine learning and deep learning techniques in real-world scenarios, enabling users to effectively handle time series data. This guide is not only informative but also structured to facilitate learning through practical examples and thorough explanations.

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Pros

  • Comprehensive coverage of time series analysis techniques
  • Suitable for both beginners and experienced users
  • Hands-on examples with PyTorch and Pandas
  • Extensive print length for detailed exploration
  • Latest edition includes updated methodologies

Kamchiliklari

  • A bit heavy for casual reading

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Xususiyatlar va Afzalliklar

  • Learn traditional and advanced techniques for time series forecasting.
  • Hands-on practical examples to improve forecasting accuracy.
  • Includes free eBook with print or Kindle purchase.
  • Covers deep learning models including RNNs and transformers.
  • Ideal for professionals and students in various industries.
  • New edition features enhancements in transformer architectures and probabilistic forecasting.

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